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Internships
Internship Information and Resources
DSMMA trainees have conducted internships at the following locations.
Allianz Life
Accenture
Argonne National Labs
Caltech
Center for Computational Astrophysics, Flatiron Institute
Duke University (ColAI: AI Exchange Learning Platform)
General Mills
Goddard Space Flight Center - NASA
Image Sensing Systems
Infinite Campus
LI-COR Environmental
Los Alamos National Labs
Massachusetts Institute of Technology
Medtronic
National Center for Supercomputing Applications (NCSA) at University of Illinois at Urbana-Champaign
Optum Labs (United Health Group)
Seagate Technologies
Space Telescope Science Institute
The Resource Group
Traveler's Insurance
University of Illinois Urbana-Champaign Students Pushing INnovation (SPIN) Program
University of Maryland- Baltimore
UMASS Dartmouth
University of Minnesota
Biostatistics Department
Department of Computer Science and Engineering
School of Physics and Astronomy
School of Statistics
Zooniverse
Courses and Minor Degrees
Students receiving an NRT stipend and participating in the Data Science in Multi-Messenger Astrophysics NRT program will be required to complete the relevant coursework in this field.
For both the M.S. and Ph.D. students, the following courses will be required:
AST 5731 / STAT 5731 - Bayesian Astrostatistics (4 credits) - Syllabus
AST 8581 / PHYS 8581 / CSCI 8581/ STAT 8581 - Big Data in Astrophysics (4 credits) - Syllabus
Ph.D. students will also be required to complete 4 credits of electives. The elective course list can be found below. Note that these 4 credits could be earned by doing research, e.g. through AST 8990, PHYS 8994 or STAT 8992 or a similar course. Please contact the Astrophysics Director for Graduate Studies for further information.
Completing the above course requirements suffices to receive the minor graduate (M.S. or Ph.D.) degree in Data Science in Astrophysics.
Students may choose electives from the following list or consult with the Astrophysics Director of Graduate Studies for additional options:
AST 5022 - Relativity, Cosmology, and the Universe
AST 8001 - Radiative Processes in Astrophysics
AST 8011 - High Energy Astrophysics
AST 8990 - Research in Astronomy and Astrophysics
CSCI 5521 - Introduction to Machine Learning (formerly Pattern Recognition)
CSCI 5523 - Introduction to Data Mining
CSCI 5525 - Machine Learning
CSCI 5609 - Visualization
CSCI 5707 - Principles of Database Systems
EE 5239 - Introduction to Nonlinear Optimization
EE 5251 - Optimal Filtering and Estimation
EE 5531 - Probability and Stochastic Processes
EE 5542 - Adaptive Digital Signal Processing
EE 5561 - Image Processing and Applications
EE 5571 - Statistical Learning and Inference
EE 8591 - Predictive Learning from Data
MATH 5587 - Elementary PDE 1
PHYS 5022 - Cosmology, Universe
PHYS 5980 - Introduction to Research Seminar
PHYS 8501 General Relativity and Cosmology
PHYS 8502 General Relativity and Cosmology II
PHYS 8611 - Cosmic Rays and Plasma Astrophysics
PHYS 8900 - Elementary Particle Physics
PHYS 8994 - Research in Physics
PUBH 7460 - Advanced Statistical Computing
PUBH 8442 - Bayesian Decision Theory
STAT 5302 - Applied Regression Analysis
STAT 5401 - Applied Multivariate Methods
STAT 5421 - Analysis of Categorical Data
STAT 5511 - Time Series Analysis
STAT 5601 - Nonparametric Methods
STAT 8051 - Applied Statistical Methods 1: Computing and Generalized Linear Models
STAT 8913 - Literature Seminar
STAT 8931 - Advanced Topics in Statistics
STAT 8992 - Directed Readings and Research
The selection of the elective course(s) must be done in consultation with the Astrophysics Director of Graduate Studies, and must be compatible with the student’s major degree requirements.
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